计算机应用 ›› 2014, Vol. 34 ›› Issue (10): 2938-2943.DOI: 10.11772/j.issn.1001-9081.2014.10.2938

• 虚拟现实与数字媒体 • 上一篇    下一篇

基于增强微结构和上下文相似度的图像检索

胡扬波1,袁杰1,王李冬2   

  1. 1. 江苏电力信息技术有限公司,南京210024;
    2. 杭州师范大学 钱江学院,杭州 310018
  • 收稿日期:2014-03-28 修回日期:2014-06-08 出版日期:2014-10-01 发布日期:2014-10-30
  • 通讯作者: 袁杰
  • 作者简介:胡扬波(1964-),男,江苏无锡人,高级工程师,硕士,主要研究方向:图像处理、数据挖掘;
    袁杰(1981-),男,湖北麻城人,工程师,博士,主要研究方向:图像处理、模式识别、信息检索;
    王李冬(1982-),女,浙江温州人,讲师,博士,主要研究方向:文本分析、语义挖掘、信息检索。

Image retrieval based on enhanced micro-structure and context-sensitive similarity

HU Yangbo1,YUAN Jie1,WANG Lidong2   

  1. 1. Jiangsu Electric Power Information Technology Company Limited, Nanjing Jiangsu 210024, China;
    2. Qianjiang College, Hangzhou Normal University, Hangzhou Zhejiang 310018, China
  • Received:2014-03-28 Revised:2014-06-08 Online:2014-10-01 Published:2014-10-30
  • Contact: YUAN Jie

摘要:

针对图像检索中多特征综合描述子维度过高且综合权值难以确定的缺点,提出一种新的基于增强微结构和上下文相似度的图像检索方法。首先,使用一种新的局部模式映射来创建过滤图;然后,基于该图上的颜色共生关系提取增强微结构描述子,该描述子综合了多种特征而维度与单特征相同,检索时使用此描述子计算图像对间的规范距离得出初始的有序相似图像序列;最后,结合迭代上下文相似度对检索序列进行重新排序。当迭代次数为50且考虑前24幅结果图像时,在Corel-5000和Corel-10000图像集上的实验结果显示,所提方法与同类型的多重基元直方图(MTH)和微结构描述子(MSD)方法相比,检索查准率分别提高了13.14%、7.09%和11.03%、6.8%。结果表明新方法能在维度不变的情况下综合多种特征并充分利用上下文信息,从而有效提高图像检索的准确率。

Abstract:

A new image retrieval method based on enhanced micro-structure and context-sensitive similarity was proposed to overcome the shortcoming of high dimension of combined image feature and intangible combined weights. A new local pattern map was firstly used to create filter map, and then enhanced micro-structure descriptor was extracted based on color co-occurrence relationship. The descriptor combined several features with the same dimension as single color feature. Based on the extracted descriptor, normal distance between image pairs was calculated and sorted. Combined with the iterative context-sensitive similarity, the initial sorted image series were re-ranked. With setting the value of iteration times as 50 and considering the top 24 images in the retrieved image set, the comparative experiments with Multi-Texton Histogram (MTH) and Micro-Structure Descriptor (MSD) show that the retrieval precisions of the proposed algorithm respectively are increased by 13.14% and 7.09% on Corel-5000 image set and increased by 11.03% and 6.8% on Corel-10000 image set. By combining several features and using context information while keeping dimension unchanged, the new method can enhance the precision effectively.

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